InterleavedRB¶

class InterleavedRB(interleaved_element, physical_qubits, lengths, backend=None, num_samples=3, seed=None, full_sampling=False, circuit_order='RIRIRI')[source]¶

An experiment to characterize the error rate of a specific gate on a device.

Overview

Interleaved Randomized Benchmarking (RB) is a method to estimate the average error-rate of a certain quantum gate.

An interleaved RB experiment generates a standard RB sequences of random Cliffords and another sequence with the interleaved given gate. After running the two sequences on a backend, it calculates the probabilities to get back to the ground state, fits the two exponentially decaying curves, and estimates the interleaved gate error. See Ref. [1] for details.

References

User manual

Randomized Benchmarking

Analysis class reference

InterleavedRBAnalysis

Experiment options

These options can be set by the set_experiment_options() method.

Options

Defined in the class InterleavedRB:
- circuit_order (str)
  
  Default value: "RIRIRI"
  
  How to order the reference and the interleaved circuits. "RIRIRI" (alternate a reference and an interleaved circuit) or "RRRIII" (push all reference circuits first, then all interleaved ones).
Defined in the class StandardRB:
- lengths (List[int])
  
  Default value: None
  
  A list of RB sequences lengths.
- num_samples (int)
  
  Default value: None
  
  Number of samples to generate for each sequence length.
- seed (None or int or SeedSequence or BitGenerator or Generator)
  
  Default value: None
  
  A seed used to initialize numpy.random.default_rng when generating circuits. The default_rng will be initialized with this seed value every time circuits() is called.
- full_sampling (bool)
  
  Default value: None
  
  If True all Cliffords are independently sampled for all lengths. If False for sample of lengths longer sequences are constructed by appending additional Clifford samples to shorter sequences.
- clifford_synthesis_method (str)
  
  Default value: "rb_default"
  
  The name of the Clifford synthesis plugin to use for building circuits of RB sequences. See Synthesis Methods.
Defined in the class BaseExperiment:
- max_circuits (Optional[int])
  
  Default value: None
  
  The maximum number of circuits per job when running an experiment on a backend.

Example

import numpy as np
from qiskit_experiments.library import StandardRB, InterleavedRB
from qiskit_experiments.framework import ParallelExperiment, BatchExperiment
import qiskit.circuit.library as circuits

lengths = [1, 2, 4, 8] + np.arange(10, 80, 10).tolist()
num_samples = 3
seed = 1010
qubits = (1, 2)

int_exp2 = InterleavedRB(
    circuits.CXGate(), qubits, lengths, num_samples=num_samples, seed=seed)

int_expdata2 = int_exp2.run(backend=backend).block_for_results()
int_results2 = int_expdata2.analysis_results(dataframe=True)
display(int_expdata2.figure(0))

print(f"Available results: {set(int_results2.name)}")

../_images/qiskit_experiments.library.randomized_benchmarking.InterleavedRB_1_0.png

Available results: {'alpha_c', 'EPC', 'alpha'}